Research on Adaptive Cruise Control Car-following Model Based on Dynamic Spacing in V2X Scenario

Abstract

In the adaptive cruise control (ACC) car-following model, the constant spacing strategy cannot adapt to complex and variable deceleration and acceleration situations. When the preceding car decelerates or accelerates suddenly, considering the safety and adaptability, the desire spacing should be larger or smaller, so the desire spacing is not only related to the speed of the two cars, but also to the speed change of the preceding car. For this problem of the deficiency, which the desire spacing existed, an adaptive cruise control car-following model based on dynamic headway strategy is proposed in this paper. In order to achieve more realtime and more accurate information transmission, this paper uses the v2v communication in v2x environment to obtain the preceding car information. MATLAB/Simulink is used to simulation modelling for verification and analysis. The experimental results show that, under the same simulation conditions, the dynamic spacing strategy proposed in this paper have a larger desire spacing for safety when preceding car decelerates, and a smaller desire spacing for comfort and road dynamic utilization when preceding car accelerates. So, the dynamic spacing strategy proposed in this paper shows different improvement effects for different acceleration and deceleration conditions.

Multi-State Car-Following Behavior Simulation in a Mixed Traffic Flow for ICVs and MDVs

“…Thus, these will provide a reference for formulating reasonable and safe control strategies. The simulation objects of available studies include theoretical models (e.g., a family of neural-network-based car-following models), designed physics-informed deep learning car-following model (PIDL-CF) architectures encoded with four popular physics-based models [28], traffic scenes (e.g., cautious, normal, and aggressive autonomous driving styles and their effects on important variables in traffic flow theory) [29], road networks with non-signalized intersections in a connected-vehicle environment [30], adaptive cruise control (ACC) systems for ACC vehicles [31], and novel cellular automata models for mixed traffic considering the limited visual distance to explore the influence of visibility capability and CAV market penetration on traffic efficiency [32].…”